Multi-pose Face Detection Using Facial Features and AdaBoost Algorithm
Jinxin Ruan, Junxun Yin · 2009
Multi-pose face detection has been one of difficult and hot issues in face detection research nowadays, and urgently need to be solved in practical application. In this paper, a multi-pose face detection algorithm based on facial features and AdaBoost algorithm is introduced. Making full use of facial skin color information firstly, the most background regions can be quickly excluded and the skin color regions can be gotten. After detecting eyes and mouth, the face candidates are segmented according to face orientation decided by the geometric features of the eyes and mouth regions. At last, the face candidates are verified by AdaBoost algorithm. The experimental results demonstrate that the algorithm can further improve the multi-pose face detection accuracy and is highly robust to facial expression and occlusion.